Paper Presentations: Hospital-Acquired Conditions and Challenges — Avoiding the Bite: Implementation of the St. Jude Advanced Warning Score (sJAWS) System (204-2)

3:50 – 4:10 pm Thursday, September 13

1CH  Eight and a half percent to fourteen percent of all in-hospital cardiopulmonary arrests in children occur outside the intensive care unit (ICU), and the mortality rate for these patients is 50%–67% (Murray, Williams, Pignataro, & Volpe, 2015), making Pediatric Early Warning Scoring (PEWS) systems a high priority for hospitals. After identifying a need for timely identification and treatment of at-risk patients, a multidisciplinary team was formed to design, implement, educate, and monitor a customized assessment tool and algorithm.

The team evaluated published tools, performed a literature review, and benchmarked with pediatric hospitals. Based on the findings, a tool (St. Jude Advanced Warning Score – sJAWS) and algorithm were developed to meet the needs of pediatric hematology/oncology patients. The tool was modified from the Boston Children’s Hospital Early Warning Scoring System (Agulnik et al., 2016).

A 1-month pilot was completed to evaluate the efficiency and effectiveness of the process, gather feedback on the tool, and modify the algorithm prior to hospital-wide go-live.

On-going quality improvement analysis was initiated to ensure proper scoring of patients, appropriate activation of the algorithms, and timely transfer of patients to the appropriate level of care. Rapid Response Team (RRT) and code activations were also monitored.

More than 2,000 sJAWS scores were randomly reviewed. Immediate feedback and education was provided with discovered errors. Staff suggestions during feedback were used to improve processes.

Total inpatient RRTs increased, total transfers to the PICU from RRTs increased, ICU consults increased, and sJAWS was used as an advocacy tool by the nursing staff to enhance patient safety.

The implementation of sJAWS improved the early identification and monitoring of patients and timely transfer to the appropriate level of care. Future goals include refinement of the tool and algorithm and evaluation of a tool in the outpatient department with unplanned admissions.